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A feature ensemble technology to identify molecular mechanisms for distinction between multiple subtypes of lymphoma

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Progress in Natural Science:Materials International 2008年第12期18卷 1491-1500页

作者： Yueying Yang~(a,1) Haiyun Wang~(a,b,1) Xia Li~(a,b,c) Xue Xiao~c Su Fei~a Chuanxing Li~a Hongzhi Wang~d Shaoqi Rao~(a,c,e) Yadong Wang~d a College of Bioinformatics Science and Technology,Bio-pharmaceutical Key Laboratory of Heilongjiang Province and State,Harbin Medical University,Harbin 150081,China b College of Life Science and Technology,Tongji University,Shanghai 200092,China c The Biomedical Engineering Institute,Capital Medieal University,Beijing 100054,China d Department of Computer Science,Harbin Institute of Technology,Harbin 150080,China e Department of Molecular Cardiology,Cheveland Clinic Foundation,Cleveland,OH 44195,USA College of Bioinformatics Science and Technology Bio-pharmaceutical Key Laboratory of Heilongjiang Province and State Harbin Medical University Harbin 150081 China College of Life Science and Technology Tongji University Shanghai 200092 China The Biomedical Engineering Institute Capital Medical University Beijing 100054 China Department of Computer Science Harbin Institute of Technology Harbin 150080 China Department of Molecular Cardiology Cleveland Clinic Foundation Cleveland OH 44195 USA

Due to complexities and genetic heterogeneities of biological phenotypes,robust computational approaches are desirable to achieve high generalization performance with multiple classifiers,perturbations of the data structures,and biological *** purpose of this study is to extend our developed ensemble decision approach to distinguish multiple heterogeneous phenotypes and to elucidate the underlying molecular bridges that intertwine the *** work identifies the significant molecular mechanisms (disease-relevant genes and functions) that underpin the complex molecular mechanisms for distinction between multiple phenotypes. Feature genes and hierarchical gene cores identified by our method have achieved high accuracy in the classification of multiple pheno- *** results show that the proposed analysis strategy is feasible and powerful in the classification of biological subtypes and in the explanation of the molecular connections between clinical *** interpretations with Gene Ontology revealed concerted genetic pathways for some lymphoma subtypes.

关键词： ensemble decision approach Molecular mechanisms Lymphoma Microarray

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